teckedd/gha-whisper-small-twi-v6
Twi/Akan + English retention Whisper ASR for Ghana Health AI (v6-local-holdout). Recipe v6 mix; promote=False.
- Base model:
teckedd/gha-whisper-small-twi-v6 - Task:
automatic-speech-recognition - Languages:
tw,ak,en - Card generated: 2026-08-16 (UTC)
- Product: ghanahealth.serendepify.com
Not a medical device. Outputs support community health guidance only.
Metrics
| Metric | Value |
|---|---|
val_wer | 0.2970 |
val_cer | 0.1031 |
Training data
google/WaxalNLP (aka_asr)local (ghana-health-ai-recorder)fsicoli/common_voice_22_0 (tw)fsicoli/common_voice_22_0 (en)ghananlpcommunity/twi-speech-text-multispeaker-16k (default)
Intended use
- In-product ASR / TTS / chat for Twi (Akan) and English health conversations in Ghana.
- Research on low-resource Ghanaian language speech and health dialogue.
Out of scope
- Clinical diagnosis or autonomous medical decisions.
- Claiming near-native quality without reporting held-out WER/CER or human A/B scores.
How to load
from transformers import pipeline # or AutoModel + processor per task
# repo: teckedd/gha-whisper-small-twi-v6
Citation
If you use this checkpoint, please credit Ghana Health AI / Serendepify and the upstream base model authors plus any listed datasets.
Recipe
- Run:
v6-local-holdout - Freeze encoder:
False - LR / steps / batch:
5e-06/600/8x4 - Local recorder data:
True· manifest/root/gha_local_asr/manifest.train32.jsonl· weight0.08 - Baseline to beat (v6 serving, Waxal full test greedy):
0.3149 - Beats v6 greedy: False · v6 beam5 bar (
0.3044): False - Historical reference (Round 2 greedy, superseded):
0.3283
Serving
Production decode uses num_beams=5 in modal/asr_service.py.